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  • January–February 2018
  • Article
  • Marketing Science

Some Customers Would Rather Leave Without Saying Goodbye

By: Eva Ascarza, Oded Netzer and Bruce G.S. Hardie
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Abstract

We investigate the increasingly common business setting in which companies face the possibility of both observed and unobserved customer attrition (i.e., “overt” and “silent” churn) in the same pool of customers. This is the case for many online-based services where customers have the choice to stop interacting with the firm either by formally terminating the relationship (e.g., canceling their account) or by simply ignoring all communications coming from the firm. The standard contractual versus noncontractual categorization of customer–firm relationships does not apply in such hybrid settings, which means the standard models for analyzing customer attrition do not apply. We propose a hidden Markov model (HMM)-based framework to capture silent and overt churn. We apply our modeling framework to two different contexts—a daily deal website and a performing arts organization. In contrast to previous studies that have not separated the two types of churn, we find that overt churners in these hybrid settings tend to interact more, rather than less, with the firm prior to churning; that is, in settings where both types of churn are present, a high level of activity—such as customers actively opening emails received from the firm—is not necessarily a good indicator of future engagement; rather it is associated with higher risk of overt churn. We also identify a large number of “silent churners” in both empirical applications—customers who disengage with the company very early on, rarely exhibit any type of activity, and almost never churn overtly. Furthermore, we show how the two types of churners respond very differently to the firm’s communications, implying that a common retention strategy for proactive churn management is not appropriate in these hybrid settings.

Keywords

Churn; Retention; Attrition; Customer Base Analysis; Hidden Markov Models; Latent Variable Models; Customer Relationship Management; Consumer Behavior

Citation

Ascarza, Eva, Oded Netzer, and Bruce G.S. Hardie. "Some Customers Would Rather Leave Without Saying Goodbye." Marketing Science 37, no. 1 (January–February 2018): 54–77.
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About The Author

Eva Ascarza

Marketing
→More Publications

More from the Authors

    • 2022
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    When Less Is More: Using Short-term Signals to Overcome Systematic Bias in Long-run Targeting

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    By: Eva Ascarza
More from the Authors
  • When Less Is More: Using Short-term Signals to Overcome Systematic Bias in Long-run Targeting By: Ta-Wei Huang and Eva Ascarza
  • Retail Media Networks By: Eva Ascarza, Ayelet Israeli and Celine Chammas
  • Managing Customers in the Digital Era By: Eva Ascarza
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